Margaret Hall. The Imperial Aircraft Flotilla: The Worldwide Fundraising Campaign for the British Flying Services in the First World War
Bibliographic record
Abstract
I thought I knew about the First World War and the Royal Flying Corps (RFC). We go regularly to St-Omer in France, the RFC headquarters from 1914 and where the Royal Air Force (RAF) began in 1918. Yet, until I read this account by a former FCO colleague, I had no idea of the 1915–1918 Imperial aircraft campaign. The campaign sometimes had local official support but, in the main, it was voluntary efforts, often supported by the local press, that provided some 550 aircraft. Some donors wished to prove their patriotism. Others hoped for honours or advancement. For many it was a form of memorial for relatives lost in the conflict. Hall traces the impetus to the pre-war tradition of funding ‘Dreadnoughts’ for the Royal Navy. Australia, New Zealand and the Federated Malay States did so, although Canada rejected the idea. Warships were expensive; the cheapest was £150,000 in 1914. Aircraft were relatively inexpensive by comparison. One without guns – not unknown in 1914 when the main use was reconnaissance work – could be had for £1500. One with guns cost £2250, while a seaplane was £3500. Dominica in the Caribbean was first off the mark, donating one aircraft each to the RFC and the Royal Naval Air Service in the early days of the war. This led in 1915 to a campaign by the Patriotic League of Britons Overseas and the Overseas Club. Amounts donated were small at first but sufficient: ‘Overseas No. 1’ was handed over in May 1915. The response grew, with a cheque for £4500 arriving from Hong Kong, which had a long tradition of donations for Empire causes; the funds came from both Chinese and Britons. In total, Hong Kong would give £1,000,000 to the war effort. Malaya was also generous. The Malayan Air Fleet Fund was launched in March 1915 by the New Zealander Charles Alma Baker. Chinese donors were prominent, and the small Armenian and Tamil communities also contributed. Malay donations were channelled through the Sultans. By May 1916, the Federated Malay States had donated over £25,000, while the Sultan of Johor had equipped a squadron of fighters with a £31,000 donation. Expatriates in Siam (Thailand) provided five aircraft. From Shanghai and the Chinese ports came 20. All this was overshadowed by the contributions from the subcontinent.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.079 | 0.021 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".